Search Results - (( developing function method algorithm ) OR ( data simulation optimization algorithm ))
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…This research focuses on developing a novel path planning algorithm, called Generalized Laser Simulator (GLS), to solve the path planning problem of mobile robots in a constrained environment. …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2023“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…This paper�s novelty includes introducing a new method for selecting inputs and developing a new model for predicting water levels. …”
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Characterization of PV panel and global optimization of its model parameters using genetic algorithm
Published 2013“…The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module. …”
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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Modeling the powder compaction process using the finite element method and inverse optimization
Published 2011“…Thus, an integrated simulation module consisting of an inverse optimization method and a finite element method was developed for modeling the powder compaction process as a whole. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…The developed algorithm weighted the n objects contribution in explaining the separation between groups. …”
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Monograph -
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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Conference or Workshop Item -
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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Thesis -
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…Then, we apply the kernel method to the survival data. Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
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Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm
Published 2020“…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…Forward model was also involved in the process of defining the objective function. Next, using simulated data together with historical data, objective function will be computed. …”
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Final Year Project -
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Model predictive control on fed-batch penicillin fermentation process
Published 2009“…In order to obtain best optimization result for the fed-batch penicillin fermentation process, two optimization algorithms were selected. …”
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Undergraduates Project Papers -
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Smart Routing For Solid Waste Collection
Published 2023“…Finally, the conclusion highlights the accomplishments of the project, including the successful development of the route optimization algorithm and the web-based application. …”
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Final Year Project Report / IMRAD
